Efficient supervision strategy for tomographic AO systems on E-ELT

N. Doucet, D. Gratadour, H. Ltaief, E. Gendron, A. Sevin, F. Ferreira, F. Vidal, R. Kriemann, D. Keyes

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

A critical subsystem of the tomographic AO RTC is the supervisor module. Its role is to feed the challenging real-time data pipeline with a new reconstructor matrix at a regular rate, computed from a statistical analysis of the measurements, to optimize the performance of the AO system. This process involves solving a system of linear equations defined by the covariance matrix of the wave front sensors' measurements, the size of which may be up to 90k-90k for the E-ELT's First light instruments using tomographic AO modules. The computational load for the solver of this dense symmetric matrix system is quite significant at this scale but can be efficiently handled using state-of-the-art energy-efficient manycore x86 or accelerator-based architectures, such as KNLs or GPUs, respectively. As part of the Green Flash project, we develop a supervisor module and demonstrate its portability by deploying it on each aforementioned hardware system. Finally, we describe different implementations and their trade-offs in terms of performance and accuracy and show preliminary results on the possible impact of hierarchically low-rank approximation methods on the overall supervisor module.

Original languageEnglish (US)
DOIs
StatePublished - Jan 1 2017
Event5th Adaptive Optics for Extremely Large Telescopes, AO4ELT 2017 - Tenerife, Canary Islands, Spain
Duration: Jun 25 2017Jun 30 2017

Conference

Conference5th Adaptive Optics for Extremely Large Telescopes, AO4ELT 2017
CountrySpain
CityTenerife, Canary Islands
Period06/25/1706/30/17

Keywords

  • AO
  • Dense linear algebra
  • ELT
  • High performance computing
  • Low-rank approximations
  • MOAO
  • Many-core Architectures
  • RTC
  • Tomography

ASJC Scopus subject areas

  • Space and Planetary Science
  • Mechanical Engineering
  • Control and Systems Engineering
  • Instrumentation
  • Astronomy and Astrophysics
  • Electronic, Optical and Magnetic Materials

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